PORTFOLIO MANAGEMENT WITH ESG NEWS SENTIMENT

Auteurs

  • Stéphane GOUTTE Université Paris Saclay, UMI SOURCE, IRD, UVSQ, France; Paris School of Business, France
  • Ron GROSSE Braunschweigische Landessparkasse, Germany
  • Hoang-Viet LE Keynum Investments, France Université Paris Saclay, UMI SOURCE, IRD, UVSQ, France Corresponding author: Hoang-Viet Le
  • Fei LIU IPAG Business School, France
  • Hans-Jörg VON METTENHEIM IPAG Business School, France; Keynum Investments, France; Oxford-Man Institute of Quantitative Finance, United Kingdom

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https://doi.org/10.54695/bmi.172.0072

Mots-clés:

ESG, Stock Market Prediction, Sentiment Analysis, News, Big Data.

Résumé

In this paper, we introduce a novel news sentiment database and analyze its potential applications in the financial markets via several trading experiments. We analyze the predictability of the news sentiment (both general news and ESG-related news) on the return of European stocks and the potential of applying them as a proper trading strategy over seven years from 2015 to 2023. We find that sentiment indicators such as Tone, and Polarity show significant relationships to the return of the stock price. Those relationships can be exploited, even in the most naive way, to create trading strategies that can be profitable and outperform the market. Furthermore, among the indicators, those extracted from ESG-related news tend to show better performance. This sentiment database is available through a bespoke app at the website https://esg.cafe

Publiée

2023-04-01

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